A System Dynamics Simulation Applied to Healthcare: A Systematic Review.

Mohammad Reza Davahli,Waldemar Karwowski,Redha Taiar

doi:10.3390/ijerph17165741

Mohammad Reza Davahli, Waldemar Karwowski + Show 1 more

Open Access

https://doi.org/10.3390/ijerph17165741

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Abstract

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models’ quality were discussed.

Highlights

Complex and intractable healthcare problems, as well as limited progress in discovering effective solutions, continue to challenge the healthcare industry [1,2]
Simulation modeling is considered to be a wise option because the complexities of problems are far beyond our capacity to solve them manually [6]
The main objective of the present study is to review recent papers that utilize the system dynamics (SD) method to analyze a variety of healthcare problems

Summary

Introduction

Complex and intractable healthcare problems, as well as limited progress in discovering effective solutions, continue to challenge the healthcare industry [1,2]. Many internal and external factors that influence healthcare outcomes are often nonlinear [3,4,5,6,7]. Under these conditions, simulation models can help to elucidate the counterintuitive behavior of complex healthcare problems [6]. According to Sterman [6], it is challenging to develop accurate healthcare simulation models because there is no reliable and well-understood principle in this area. The substantial benefits of developing and applying simulation models are learning about complex problems and testing different interventions [6].

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Conclusion